ABSTRACT Alzheimer's disease (AD) remains a leading cause of disability and death in the US and major global public health problem due to rise in aging population resulting in untold suffering, and severe challenges to health care systems and economies is certain. Solutions will come only from innovative research. Our application is highly responsive to this urgent scientific need by proposing to leverage an innovative molecular imaging platform invented at Stanford, multiplexed ion beam imaging (MIBI). We will determine the high dimensional cellular and subcellular protein-level expression, interaction, and localization for AD-relevant molecules identified by genomic and proteomic studies in resilience and pathologic states using human brain sections from an ongoing proteomic investigation of AD. We hypothesize that in-depth, stage-specific phenotypic signatures extracted from these unique groups will provide insight into the modifiable factors that endorse the protective mechanisms of brain reserve. We will test our hypothesis through three Specific Aims: (1) Establish a subcellular, phenotypic framework of vulnerable and resistant brain areas. Next-generation MIBI equipment will be used to rigorously image 30+ proteins simultaneously; targets marking subtypes of neurons, synapses, non-neuronal cells, neuro-inflammatory, and vascular components will be concurrently measured. (2) Reveal cognitive resilience multiplexed phenotypes. Using approaches we have successfully applied in other single cell studies, we will analyze multiplexed imaging data with statistical deep learning methods already established in our lab to identify topological, cellular, and molecular phenotypic differences among resilient, co- morbid, and AD dementia. (3) Implement a shared data repository. The power of multiplexed imaging in biology is its ability to reveal co-localization or mutual exclusivity to infer regulatory roles and gain mechanistic insight. To disseminate hundreds of these images from our proposed highly multiplexed study, we will create a web-based portal, using already established infrastructure, where all of the images from this study can be accessed, multi-color overlays generated ad hoc, and all the features will be shared freely.